CAREER: Complexity From Simplicity: Multi-scale Computational Deciphering of the Viral Life Cycle

该奖项全部或部分由2021年美国救援计划法案（公法117- 2）资助。埃博拉病毒和SARS-CoV-2等病毒通过多种病毒蛋白的联合作用传播并引起疾病。限制病毒在患者体内的繁殖需要全面了解所有这些蛋白质如何在一个受感染的细胞中以及在我们体内的许多细胞中共同发挥作用。该项目将使用实验数据和计算机模拟相结合，以了解和预测驱动埃博拉病毒感染的复杂相互作用。这样的理解将允许识别这种蛋白质网络中的任何弱点，这些弱点可以被新药靶向。该项目还将开发新的研究工具，以促进计算机模拟的使用，加速病毒研究。该项目的教育目标将通过培训下一代科学家（从高中到研究生水平）来补充研究目标，使他们能够随时联合收割机结合计算和实验研究方法。研究和教育目标将使人们能够全面了解埃博拉病毒生物学、综合计算/实验研究工具以及能够利用计算技术促进公共卫生的科学工作者队伍。本提案的总体目标是确定驱动病毒复制和在宿主内传播的相互关联的亚细胞和细胞间机制，使用埃博拉病毒作为模型系统。机械计算模型是生成真实的生物系统的虚拟版本的强大工具，以实现复杂系统级动力学的分析。在这个项目中，与实验数据紧密结合的机械计算模型将用于确定埃博拉病毒繁殖的关键机制。将开发新的多维分析来阐明耦合机制，并将通过实验测试计算预测。研究目标将量化：1）使用常微分方程系统在亚细胞水平上单个蛋白质动力学对病毒产生的影响; 2）使用基于代理的模型在细胞间病毒传播和增殖的细胞间过程的时空影响;和3）使用多尺度模拟跨尺度的亚细胞和细胞间机制对病毒复制的组合影响。这些模拟将根据埃博拉病毒微型基因组系统的实验数据进行校准和验证，该系统允许仔细分离单个病毒蛋白质和病毒生命周期中的步骤（例如转录和组装）。研究目标将支持生物学和计算交叉点的教育目标。教育目标将：以可获得和可持续的方式将定量方法纳入现有的生物学课程;并在本科生物医学工程学生中进行跨学科培训。这些目标将通过多层次的教育方法来实现，这种方法将高中、本科和研究生各级内部和之间的学生和教师联系起来。该项目将开发：1）生物学课程的定量学习模块; 2）国际跨学科本科课程; 3）研究生的跨学科研究培训。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117- 2).Viruses like Ebola and SARS-CoV-2 spread and cause disease through the combined action of multiple viral proteins working together. Limiting viral reproduction in patients will require a holistic view of how all of these proteins work together in one infected cell and across many cells in our bodies. This project will use a combination of experimental data and computer simulations to understand and predict the complex interactions that drive Ebola virus infection. Such an understanding will allow the identification of any weak points in this protein network that can be targeted with new drugs. The project will also develop new research tools to advance the use of computer simulations to accelerate viral research. The educational objectives of the project will complement the research objectives by training the next generation of scientists (from high school to graduate student level) to readily combine computational and experimental research methods. Together, the research and educational objectives will enable a comprehensive understanding of Ebola virus biology, integrated computational/experimental research tools, and a scientific workforce that can take advantage of computational technology to advance public health.The overall objective of this proposal is to identify interconnected subcellular and inter-cellular mechanisms that drive viral replication and spread within a host, using Ebola virus as a model system. Mechanistic computational models are powerful tools that generate virtual versions of real biological systems, to enable analysis of complex systems-level dynamics. In this project, mechanistic computational models, closely integrated with experimental data, will be used to identify key mechanisms in Ebola virus reproduction. New multi-dimensional analyses will be developed to elucidate coupled mechanisms, and computational predictions will be tested experimentally. Research objectives will quantify: 1) the impact of individual protein dynamics on viral production at the subcellular level using systems of ordinary differential equations; 2) the spatio-temporal impact of inter-cellular processes on cell-to-cell viral spread and proliferation using agent-based models; and 3) the combined impact of subcellular and inter-cellular mechanisms on viral replication across scales using multi-scale simulations. These simulations will be calibrated to and validated against experimental data from the Ebola virus minigenome system that allows careful isolation of individual viral proteins and steps in the viral life-cycle (e.g. transcription and assembly). The research objectives will support educational objectives at the intersection of biology and computation. The educational objectives will: integrate quantitative methods into existing biology curricula in an accessible and sustainable way; and advance interdisciplinary training in undergraduate biomedical engineering students. These objectives will be accomplished through a multi-tiered educational approach that connects students and teachers within, and between, high-school, undergraduate and graduate levels. The project will develop: 1) quantitative learning modules for biology courses; 2) international interdisciplinary undergraduate courses; and 3) interdisciplinary research training for graduate students.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.